sparksql json 合并json数据

java

 public class Demo {
     private static SparkConf conf = new SparkConf().setAppName("demo").setMaster("local");
     private static JavaSparkContext jsc = new JavaSparkContext(conf);
     private static SparkSession session = new SparkSession(jsc.sc());

     public static void main(String[] args) {

         // 加载students.json name,score
         Dataset<Row> score = session.read().json("./src/main/java/cn/tele/spark_sql/json/students.json");

         score.createOrReplaceTempView("scoreView");

         // name,score
         JavaRDD<Row> scoreRDD = session.sql("select * from scoreView where score > 80").javaRDD();

         // 创建信息json name,age
         JavaRDD<String> infoRDD = jsc.parallelize(Arrays.asList("{\"name\":\"Leo\",\"age\":18}",
                 "{\"name\":\"Marry\",\"age\":19}", "{\"name\":\"Jack\",\"age\":20}"));

         Dataset<Row> info = session.read().json(infoRDD);
         info.createOrReplaceTempView("infoView");

         // 拼接sql
         List<Row> scoreList = scoreRDD.collect();

         String sql = "select * from infoView where name in (";
         for (int i = 0; i < scoreList.size(); i++) {
             sql += "'" + scoreList.get(i).getAs("name") + "'";
             if (i < scoreList.size() - 1) {
                 sql += ",";
             }
         }

         sql += ")";

         // 查询 分数>80的学生的name,age

         // 转换
         JavaPairRDD<String, Integer> tempRDD = session.sql(sql).javaRDD()
                 .mapToPair(new PairFunction<Row, String, Integer>() {

                     private static final long serialVersionUID = 1L;

                     @Override
                     public Tuple2<String, Integer> call(Row t) throws Exception {
                         return new Tuple2<String, Integer>(t.getAs("name"), Integer.valueOf(t.getAs("age").toString()));
                     }
                 });

         JavaPairRDD<String, Integer> scoreRDD2 = scoreRDD.mapToPair(new PairFunction<Row, String, Integer>() {

             private static final long serialVersionUID = 1L;

             @Override
             public Tuple2<String, Integer> call(Row t) throws Exception {
                 return new Tuple2<String, Integer>(t.getAs("name"), Integer.valueOf(t.getAs("score").toString()));
             }
         });

         // join
         JavaPairRDD<String, Tuple2<Integer, Integer>> resultRDD = tempRDD.join(scoreRDD2);

         // 遍历
         resultRDD.foreach(new VoidFunction<Tuple2<String, Tuple2<Integer, Integer>>>() {

             private static final long serialVersionUID = 1L;

             @Override
             public void call(Tuple2<String, Tuple2<Integer, Integer>> t) throws Exception {
                 System.out.println("name:" + t._1 + "," + "age:" + t._2._1 + ",score:" + t._2._2);
             }
         });

         // 保存为json格式
         StructType schema = DataTypes
                 .createStructType(Arrays.asList(DataTypes.createStructField("name", DataTypes.StringType, false),
                         DataTypes.createStructField("age", DataTypes.IntegerType, false),
                         DataTypes.createStructField("score", DataTypes.IntegerType, false)));

         JavaRDD<Row> rowRDD = resultRDD.map(new Function<Tuple2<String, Tuple2<Integer, Integer>>, Row>() {

             private static final long serialVersionUID = 1L;

             @Override
             public Row call(Tuple2<String, Tuple2<Integer, Integer>> v1) throws Exception {
                 return RowFactory.create(v1._1, Integer.valueOf(v1._2._1), Integer.valueOf(v1._2._2));
             }
         });

         Dataset<Row> resultDS = session.createDataFrame(rowRDD, schema);

         resultDS.write().format("json").mode(SaveMode.Append).save("./src/main/java/cn/tele/spark_sql/json/result");

         session.stop();
         jsc.close();
     }
 }

scala

 object Demo {
   def main(args: Array[String]): Unit = {
     val conf = new SparkConf().setAppName("demo").setMaster("local")
     val sc = new SparkContext(conf)
     val sqlContext = new SQLContext(sc)

     //加载score 信息
     val scoreDF = sqlContext.read.json("./src/main/scala/cn/tele/spark_sql/json/students.json")

     scoreDF.createOrReplaceTempView("scoreView")

     val arr = sqlContext.sql("select * from scoreView where score > 80").rdd.collect()

     //创建 学生信息
     val infoRDD = sc.parallelize(Array(
       "{\"name\":\"Leo\",\"age\":20}",
       "{\"name\":\"Marry\",\"age\":30}",
       "{\"name\":\"Jack\",\"age\":21}"), 2)

     val infoDS = sqlContext.read.json(infoRDD)

     infoDS.createOrReplaceTempView("infoView")

     var sql = "select * from infoView where name in ("
     //拼接sql
     for (i <- 0 to arr.length - 1) {
       sql += "'" + arr(i).getAs[String]("name") + "'"
       if (i < arr.length - 1) {
         sql += ","
       }
     }

     sql += ")"

     val tempRDD = sqlContext.sql(sql).rdd.map(row => {
       (row.getAs[String]("name"), row.getAs[Long]("age").toInt)
     })

     val tempRDD2 = scoreDF.rdd.map(row => {
       (row.getAs[String]("name"), row.getAs[Long]("score").toInt)
     })

     //join
     val resultRDD = tempRDD.join(tempRDD2)

     //遍历
     resultRDD.foreach(t => {
       println("name:" + t._1 + "age:" + t._2._1 + "score:" + t._2._2)
     })

     val rowRDD = resultRDD.map(t => Row(t._1, t._2._1, t._2._2))

     //保存为json文件
     val schema = DataTypes.createStructType(Array(
       StructField("name", DataTypes.StringType, false),
       StructField("age", DataTypes.IntegerType, false),
       StructField("score", DataTypes.IntegerType, false)))

     val df = sqlContext.createDataFrame(rowRDD, schema)

     df.write.format("json").mode(SaveMode.Append).save("./src/main/scala/cn/tele/spark_sql/json/result")
   }
 }